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232 = 232 –  2 raised to the power of 32.
Bad RNG – It is a RNG, which will not form a RandSeeds circle.
C1 – first constant of the formula LCG RNG.
C2 – The second constant of the formula LCG RNG.
Casino Software Provider- A company that provides software and supporting server for theonline casinos. Most popular casino software providers are micro gamming, Playtech and RTG (Real Time Gaming).
Good RNG – It is a RNG, which will form a RandSeeds circle.
Mod – Operation Module. 5 mod 3 = 2; 7 mod 3 = 1.
RandSeed – A variable that stores the number from which you get the result at the casino.
RNG – Random Number Generator.
RNG Circle – The circle that is made by the formula LCG RNG.
TST – Technical Systems Testing (TST) is an Accredited internationally recognized test.
Facility (ATF) offering a full range of testing and consultation services for industries / terrestrial) and interactive gambling, betting, lotteries, traditional terrestrial eCommerce and Information Technology, in order to ensure that the game runs in a way that is fair, secure and auditable.

Random Number Generation -There are many theories of random numbers. Here I have selected the best known methods for obtaining random numbers and then I’ll show you how the casinos have random numbers and how to generate them.
In order to understand all the terms, which I will use to explain everything, I will tell you a bit ‘of history.

Many applications of randomness have led to many different methods to generate random data. these methods may vary as to how unpredictable or statistically random they are, and how quickly they can generate random numbers.
Before the advent of computational random number generators, generating large amounts of sufficiently random numbers (important in statistics) required a lot of work. Results would sometimes be collected and distributed as random number tables.

The first methods for generating random numbers – dice, coin flipping, roulette are still in use today, especially in games and gambling, as they tend to be too slow for in statistics and encryption applications.
Some physical phenomena, such as thermal noise zener diodes appear to be truly random and can be used as the basis for hardware random number generators. However, many mechanical phenomena are asymmetries and biases that make their results do not truly random. the many successful attempts to exploit these phenomena by gamblers, especially in roulette and blackjack are evidence of these effects.

Computational Methods

Hardware random number generator in computer science, a hardware random number generator is a device that generates random numbers from a physical process. these devices are typically based microscopy c phenomena such as thermal noise or the photoelectric effect or other quantum phenomena.
These processes are, in theory, completely unpredictable, and the claims of the theory of these processes are, in theory, completely unpredictable, and the claims of the theory of unpredictability are subject to experimental verification. a generator of random quantum numbers based hardware typically contains an amplifier to bring the output of the physical process in the macroscopic realm, and a transducer to convert the output into a digital signal.

It is very easy misconstruct devices that generate random numbers. In addition, they break in silence, often producing less and less random numbers as they degrade. An example would be the rapid decrease in radioactivity of the smoke detectors previously mentioned. the radiation intensity decreases, its sensor will be required to make good, is not an easy task accomplished. failure modes in such devices are plentiful and are neither easy nor quick nor cheap to detect.
Because they are quite fragile, and fail silently, statistical tests on their way out should be carried out continuously. many, but not all, such devices include some such tests in the software which reads the device.


Most of the computer “random number generators” are not hardware devices, but are routine algorithms implementing software. Often they are equipped with such a system software as language compilers (for example, as one or more library routines) or operating systems (for example, as system calls).
Linear congruential generators (LCGs) represent one of the generator algorithms oldest pseudo-random numbers and best -known. The theory behind them is easy to understand, and are easily implemented and fast.
LCGs are defined by the recurrence relation:
V j + 1 = (x Vj + B) mod M
Where Vn is the sequence of random values, and A, B and M are integer constants specific generators d ‘. mod is the module operation.
The period of a general LCG is at most M, and in many cases less. The LCG will have a period of complete if:
1. B and M are the first 2. A-1 is divisible by all prime factors of M. 3. A-1 is a multiple of 4 if M is a multiple of 4. 4 M> max (A, B, V0 ) 5. A> 0, B> 0
This is the fastest, he has evaluated all random number generators; Also successfully pass.
diehard tests: The tests are irreducible a battery of statistical tests to measure the quality of a set of random numbers. They were developed by George Marsaglia course of several years, and the first published in 1995 on a random number CD-ROM. Collectively they are considered one of these tests known stricter.
The tests are:
Birthday Distance: Choose random points on a large time interval. The spacing between the points should be asymptotically Poisson. The name is based on the birthday paradox.
Overlapping permutations: Analyze sequences of five consecutive random numbers. The 120 possible arrangements should statistically occur with equal probability. Ranks of matrices: Select a number of bits from a number of random numbers to form a matrix of {0,1}, and then determine the rank of the matrix. Counting the ranks.
Test Monkey: Treat sequences of a given number of bits as “words.” Count the words overlap in a stream. The number of “words” that should not appear to follow a known distribution. The name is based on the infinite monkey theorem.
Count 1: count the 1 bits in each of the next byte or is chosen. Convert “letters counts”, and count the instances of five -Letter “words.” Test Parking: Randomly place the circles of units in a 100 x 100 square. If the circle overlaps an existing one, please try again. After 12,000 attempts, the number of successful “parked” circles should follow a certain normal distribution.
minimum test distance: Randomly placed 8,000 points in a square of 10,000 x 10,000, then find the minimum distance between pairs. The square of this distance has to be distributed exponentially with a certain average.
Random testing Balls: randomly selects 4,000 points in an onboard 1,000 cube. Hitting a ball on every point, whose radius is the minimum distance to another point. The volume of the smallest sphere must be exponentially distributed with a certain average. The compression test: Multiply by 231 random floating on [0,1) 1. Repeat this until reaching 100,000 times. The number of floats necessary to attain one must follow a certain distribution.
The tests overlapping sums: Generate a long sequence of floats randomly on [0,1). Add sequences of 100 consecutive wagons. The amounts are to be normally distributed with mean and characteristic sigma.
Test runs: Generate a long sequence of floats randomly on [0,1). Count up and down slopes. The counts should follow a certain distribution.
Craps test: 200,000 Play craps games, counting the victories and the number of shots per game. Each count must follow a certain distribution. As you can see Hardware random number generator pre sent numerous problems, especially when you need a quick RandSeed calculation. That’s why casinos only work with pseudo -Random generatorsThe Craps test: 200,000 Play craps games, counting the victories and the number of shots per game. Each count must follow a certain distribution. As you can see Hardware random number generator pre sent numerous problems, especially when you need a quick RandSeed calculation. That’s why casinos only work with Pseudo -Random generators
randomness Statistics
State Interior Of RNG
Not the Reproducibility
Re-Seeding And A Bicycle
Read More Here There

The RNG (Random Number Generator) of the casino is a simple recursive mathematical RandSeed function (n) = ((c1 RandSeed * (n-1)) + c2) mod M, where C1, C2 two constants, factor M-Module usually 2 or 2 ^ ^ 32 64 Seeing this formula, you might think that the RandSeed continues to increase indefinitely, as we multiply the last RandSeed c1 and c2 add. In any case this does not happen and the reason for this is “M mod”. There is always a limit to the value of the RandSeed and depends on the number of bits the algorithm was run. If the job’s algorithm on 32-bit, so the range of RandSeed will -2147483648 and 2147483647. So, if the next will be greater than RandSeed +2147483647, again from -2147483648.
For example, we choose c1 and c2 = 84,783 = 4,236,381 (later you will find that is not a number can work for C1 and C2). We also RandSeed1 = 53478. After we do the calculations we get:
RandSeed2 = 243294359 = -1498047210 RandSeed3 RandSeed4 RandSeed5 = 1840508263 = -935 499 962 672 013 367 RandSeed7 RandSeed6 = = = 1645751559 -1722617994 RandSeed8 RandSeed9 RandSeed10 = = 1,156,117,926 -593,272,873 RandSeed11 = -1087751722 -1312230233 RandSeed13 RandSeed12 = 2021227526 = RandSeed14 = 837,430,135 -260,998,090 RandSeed15 RandSeed16 = = = = -1844674793 RandSeed18 RandSeed17 686,094,950 -525,319,097 -119,621,994 RandSeed20 RandSeed19 = = = 106754477 -1489495065 RandSeed21 RandSeed22 = 1806981815.
If we do this for 2 ^ 32 times we will get to RandSeed (2 ^ 32) = RandSeed1.
All the online casinos are based on this simple formula. It ‘been shown to me, a fact that I have seen as you will see below and others that the RNG casinos already cracked.
What does that a casino software provider has been approved?
Sometimes you can read that some organizations, such as TST, tested the RNG and a reliable supplier of casino software, and they said that her RNG is good. This means that only occurred if the casino is actually using this formula (RNG) in order to get the result for the user without considering the winnings he did. The casinos are not certified can use the above formula together with the winnings verification process. It ‘very simple added to the RNG algorithm, which can be made by all, to bring all users to failure at last
Here we speak only of verified casino, because casinos do not check are almost impossible to beat. They are programmed to make you lose, although this is not a rule for all so read further.
The casinos that use not only RNG. How they were beaten?
You understand very well that I can not name names here and I will not do these casinos the name, even if you ask me
Although this type of stitching unbeatable casino, were still beaten by my friend more than a year ago. At first I thought he was joking, but he was very serious and very committed to winning in a casino not verified.
First, you should know that the balance is not monitored by a human but by a program. It “takes care” of everything and makes sure that you lose your whole bankroll. It also does not make you lose the right path, but they are also programmed to make you win.
However if the user does not match a certain condition (representing the games that you play, betting that he does and the way he plays), the algorithm will not know what to do with him and he will be missed. Therefore, it depends on many factors. Knowing these factors, you can trick the algorithm and win. It ‘a type of game, but well, this was done by my friend more than a year ago.
At first he made a website of gambling and registered as an affiliate of each of these casinos. It did not make much money as an affiliate, since it was having a very low number of users and the casinos were not very well conversion. In any case it analyzed the betting process of those players, who have registered under the affiliate code, and the way in which the algorithm was making them to win and in the end to lose. So the algorithm verifies if a player has deposited a lot n it let him increase the bankroll with 40% and after that he loses all his money.
This gives you the impression that you can win in this casino, which is why after you lose everything, just that this was not your lucky day, but this casino is good. Usually this makes people to deposit more money in the same or the following day. If a player has deposited a low amount of money the algorithm does stay with the same bankroll for a while ‘and after some time the player loses. He begins to think that he had the necessary balance to win, then settles more in the casino.
After observing all these aspects (here we were not told all) of that algorithm has deposited $ 3,000 in the casino and made about $ 5,000 with the tricks, he has discovered. E ‘was surprised by the large number of unverified casinos, which have been using this algorithm, that’s why it was pleased when he finally got around to them to beat us algorithm.
The casinos, where he was playing, have already been closed. As you can see these casinos are open only for us cheat and do not care about their reputation. In addition they are intended for a small number of players.
Here’s a question:
What gives an advantage to the casino?
Because odds are always <100%?
Because odds are always <100%? The advantage depends, in particular, on every play. The advantage of roulette is the single “0” (for European Roulette) or “0 and 00” (for American roulette). It is also called the house edge. So to say that the result of the RNG can not be beaten is not correct. The idea is that the “RNG + house edge” can not be beat. Now here we are talking about how we’re going to bet RNG. At the end of the e-book will be seen as the “RNG + house edge” will be beaten to 100% by beating RNG. I say this because you know the outcome (such as the number that will land on the next lap), you’ll receive from the casino We return to the main formula of the RNG RandSeed (n) = ((c1 RandSeed * (n-1)) + c2) mod M what we need to beat the “RNG? To beat the RNG we need only two constants C1 and C2. But knowing these two constants, we will also need at least one RandSeed and so we will be able to discover the next RandSeeds, so RNG is beaten. Now let’s say we have two constants, and we know that the RandSeed for a particular ride is, for example 53,478. So c1 = 84 783, c2 = 4236381 and RandSeed1 = 53478. By doing the calculations we will know that RandSeed2 = 243,294,359. And what have we with this? So we have the RandSeed, so what? We need the number that will be held (for the game of roulette). That’s why here comes the next question. As is the format number from RandSeed? There were some people who were saying that the outcome (the number for the roulette game) comes from “RandSeed mod 37” (since there are 37 possible outcomes, such as roulette has numbers 0 … 36). This method of obtaining the result is very primitive and those who did it are really stupid. At the start I was happy because I thought I could find a way to beat the RNG. However I did not succeed. So I knew that the formula is more than just RandSeed mod for 37 or 53 (for the game of blackjack). It took me some time to find it. So I do see exactly how the number is composed of RandSeed. L et to say that we currently have a RandSeed = 1732545654. Now we will do some calculations. Run the program Calculator from Start-> Programs-> Accessories-> Calculator. Then select “scientific” from “View” menu. Enter the number RandSeed and check the radio box “Bin”
So we convert this RandSeed in binary code: 1100111010001001000110001110110 We remove the last 16 digits and so we get the following binary number: 110,011,101,000,100 If the above number has 16 digits, then you must remove the first digit of this binary number . Now we transform this binary number in decimal code (tick the “Dec” check box): 26436. E 26436 mod 37 = 18
What are the advantages of this formula gives?
This formula involves only binary operations, which are easily performed by the computer. Even this formula removes the weakness given by RandSeed mod 37.
You should tell that RandSeeds 1732545654 and 1732545655 have the same result, because we take the last 16 binary digits. And not only the next RandSeed, but also a group of 65536 (2 ^ 16) RandSeeds would give the same results in the casino. This means that a new result is to each group of 65536 RandSeeds. So, if the first group of 65,536 RandSeeds gives outcome (say the “23” number for the roulette game), then the next group will give a result (this is the next issue of the first result for the game of roulette. For our example, is the “24” number).
So the question is how RandSeed passes from one group to another. Knowing that the result will again beat RNG, as we will know which of RandSeeds group is the next one and so the result in the roulette.
So we know the formula already used to transform RandSeed in the result provided by the casino server. So all we need is to have those RandSeeds and we can safely predict the outcome. This is where we will do the research now. As we see, this simple formula is good enough to give random numbers.
But what it is quite well?
What properties should have this formula?
Why must it be exactly that?
We are going to answer these questions are still to the formula:
RandSeed (n) = ((c1 * RandSeed (n-1)) + c2) mod M
There have been many proposals before this formula appeared. The main idea was to discover the formula that would get any RandSeed once and after the last RandSeed would begin with the initial start RandSeed.
This is what I call a good RNG. Suppose you have 10
RandSeeds: 0 1 2 3 4 5 6 7 8 9. A good random number generator is 2 4 8 0 1 3 5 7 9 2 4 … A good RNG will make a circle in which each RandSeed has its place in it.
Consider the RNG circle like a roulette wheel.
Does it matter what values ​​we take for the constants?
Well, for example, if c1 is a divisor of 5 or an even number, then this formula will not make a circle. The second constant must not be “0” or “1”. The constant c2 is generally a large number. The other properties of c1 and c2 are mentioned in the first chapter. So, as you see here it is a little ‘work before making the RNG.
All the online casinos are based on this formula RNG. The dif ference between them is these two constants. Now let me tell you one thing. Knowing these two constants, the result and have the result of any online casino game. However the transformation of RandSeed in the outcome also depends on the game played. For example, it uses the same formula for both the blackjack and the roulette game, but for blackjack we “RandSeed mod by the number of cards.”
Knowing the RNG, and some results, we can find all the results in the next few minutes.

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